A high-performance induction motor drive with on-line rotortime-constant estimation

A high-performance induction motor (IM) speed drive with online adaptive rotor time-constant estimation and a proposed recursive least square (RLS) estimator is introduced in this paper. The estimation of the rotor time-constant is on the basis of the model reference adaptive system (MRAS) theory; and the rotor inertia constant, the damping constant and the disturbed load torque of the IM are estimated by the proposed RLS estimator, which is composed of an RLS estimator and a torque observer. Moreover, an integral proportional (IP) speed controller is designed online according to the estimated rotor parameters; and the observed disturbance torque is fed forward to increase the robustness of the induction motor speed drive     

A new sliding mode position controller with adaptive load torqueestimator for an induction motor

A new sliding mode control algorithm with an adaptive load torque estimator is presented to control the position of the induction motor in this paper. First, the rotor flux is estimated with the simplified rotor flux observer in the rotor reference frame and the feedback linearization theory is used to decouple the rotor position and the rotor flux amplitude. Then, a new sliding mode position controller with an adaptive load torque estimator is designed to control the position of the induction motor such that the chattering effects associated with the classical sliding mode position controller can be eliminated. Stability analysis is carried out using the Lyapunov stability theorem. Experimental results are presented to confirm the characteristics of the proposed approach. The good position tracking and load regulating responses can be obtained by the proposed position controller     

Fuzzy neural network output maximization control for sensorless wind energy conversion system

This paper presents the design of an online training fuzzy neural network (FNN) controller with a high-performance speed observer for the induction generator (IG). The proposed output maximization control is achieved without mechanical sensors such as the wind speed or position sensor, and the new control system will deliver maximum electric power with light weight, high efficiency, and high reliability. The estimation of the rotor speed is designed on the basis of the sliding mode control theory.     

Sensor-less maximum power point tracking control for wind generation system with squirrel cage induction generator

This paper proposes a technique that determines the optimal windmill operation speed and the optimal rotor flux. Moreover, the position and speed sensor-less wind generation system using the electromotive voltage observer to estimate rotor position and full-order observer to estimate rotor speed and the windmill output torque are proposed. The position and speed sensor-less maximum power point of wind power generation system is controlled by using the above estimated values, optimized windmill operation speed for maximum output power and optimized rotor flux for minimum generator losses. The effectiveness of the position and speed sensor-less maximum power point tracking control for wind power generation system with squirrel cage induction generator is verified by simulations. The simulation results confirm that the proposed method can estimate the operation speed efficiently.     

比例积分型线性超螺旋算法滑模观测器的感应电机无传感器控制

在无速度传感器感应电机调速系统中,针对滑模观测器存在滑模抖振与观测精度间的平衡问题,设计一种强鲁棒性的比例积分型线性超螺旋算法滑模观测器。首先,利用李雅普诺夫理论证明线性超螺旋算法的稳定性。然后,通过设计转子磁链观测器的中间变量,建立基于定子电流误差项的比例积分滑模面,构造出新的滑模磁链观测器。仿真与实验表明,该观测器有效抑制了滑模抖振,提升了电机的磁链观测与抗扰动能力,在电机运行时有较高的观测精度,提高了系统的动稳态性能。     

Wind turbine robust disturbance accommodating control using non-smooth H∞ optimization

Disturbance accommodating control (DAC) has been developed in the last decades for wind turbines to control the rotor/generator speed and to reduce structural loads. The method allows accommodating unknown disturbance effects by using the combination of disturbance observers and disturbance rejection controllers. The actual main problem of DAC is to define suitable disturbance observer and controller gain matrices to achieve the desired overall performance including turbine speed regulation in combination with structural load mitigation. The disturbance rejection controller is often designed and tuned separately for individual applications and operating conditions. The closed-loop system stability and uncertainties due to the use of the linearized reduced-order model in controller synthesis procedure are not fully considered. This paper introduces a method to design DAC by optimizing the observer and controller parameters simultaneously to guarantee system performance respecting to structural loads mitigation, power regulation, and robustness. To eliminate the rotor speed control steady-state error due to model uncertainties, partial integral action is included. Simulation results using NREL reference wind turbine models show that the proposed method successfully regulates the rotor speed without error despite the presence of the model uncertainties. Structural loads are also reduced using proposed method compared to DAC designed by Kronecker product method. The proposed approach is able to define a stable and robust DAC controller by solving a non-smooth H_∞ optimization problem with structure and stability constraints.     

Robust SVM-direct torque control of induction motor based on sliding mode controller and sliding mode observer

This paper proposes a design of control and estimation strategy for induction motor based on the variable structure approach. It describes a coupling of sliding mode direct torque control (DTC) with sliding mode flux and speed observer. This algorithm uses direct torque control basics and the sliding mode approach. A robust electromagnetic torque and flux controllers are designed to overcome the conventional SVM-DTC drawbacks and to ensure fast response and full reference tracking with desired dynamic behavior and low ripple level. The sliding mode controller is used to generate reference voltages in stationary frame and give them to the controlled motor after modulation by a space vector modulation (SVM) inverter. The second aim of this paper is to design a sliding mode speed/flux observer which can improve the control performances by using a sensorless algorithm to get an accurate estimation, and consequently, increase the reliability of the system and decrease the cost of using sensors. The effectiveness of the whole composed control algorithm is investigated in different robustness tests with simulation using Matlab/Simulink and verified by real time experimental implementation based on dS pace 1104 board.     

双馈感应风力发电系统低电压穿越控制

传统的双馈感应发电机(DFIG)矢量控制方案忽略了定子暂态磁通,导致当电网出现故障时控制性能恶化.为了提高电网故障下DFIG的不间断运行能力,将矢量控制与自抗扰控制器结合起来,利用扩张状态观测器估计出定子暂态磁通和电机参数误差对系统的影响并加以补偿.仿真结果表明该文提出的控制方法削弱了电网故障时DFIG的转子暂态电流峰值和电磁转矩波动,有效地保护了转子变频器和风力机机械结构,而且对电机参数误差具有鲁棒性.     

A new composite adaptive speed controller for induction motor basedon feedback linearization

A new adaptive control technique is proposed to control the speed of the induction motor in this paper. First, the rotor flux is estimated with the simplified rotor flux observer on the rotor reference frame and the feedback linearization theory is used to decouple the rotor speed and the flux amplitude. Then, a new composite adaptive control algorithm based on an integral cost function is designed to control the speed of the induction motor. The overall speed control system is verified to be stable and robust to the parameter variations and external disturbances. Experimental results are provided to demonstrate the effectiveness of the presented approach. The good speed tracking and load regulating responses can be obtained by the proposed controller     

Regulation of WTG dynamic response to parameter variations of analytic wind stochasticity

Although variable‐speed operation can reduce the impact of transient wind gusts and subsequent component fatigue, this is still an unknown factor that must now be quantified. Reduction in drive‐train stresses caused by fatigue loads in high wind turbulence is fundamental to realizing both output power leveling and long service life for a wind turbine generator (WTG). This paper presents an evolutionary controller comprising a linear quadratic Gaussian (LQG) and neurocontroller acting in tandem to effect optimal performance under high turbulence intensities, for a variable‐speed, fixed‐pitch WTG. The control objectives are maximum energy conversion and reduction in mechanical stresses on the system components. The proposed paradigm utilizes generator torque in controlling the rotor speed in relation to the highly turbulent wind speed, thereby ensuring the extracted aerodynamic power is maintained at a constant value, while shaft moments are regulated. The performance of the proposed controller is compared with that of the LQG and it is found that the former is more efficient in maintaining rated power, minimizing shaft torque variations, and shows robustness to parameter variations. Copyright © 2007 John Wiley & Sons, Ltd.     

Perturbation estimation based robust state feedback control for grid connected DFIG wind energy conversion system

This paper develops a perturbation estimation based robust state feedback control (PER-SFC) scheme of doubly-fed induction generator (DFIG) for maximum power point tracking (MPPT). The combinatorial effect of nonlinearities originally stemmed from wind turbine aerodynamics, generator modelling uncertainties and wind speed randomness is aggregated as a perturbation, which is rapidly estimated online by a sliding-mode state and perturbation observer (SMSPO). Then, a linear state feedback controller is designed to fully compensate the perturbation estimate in real-time. Furthermore, only the measurement of rotor speed and reactive power is needed while no accurate DFIG model is required by the proposed approach. Under such framework, the elegant merits of conventional linear state feedback control (favourable implementation simplicity and high reliability) and nonlinear robust control (global control consistency and considerable robustness) can be wisely incorporated. Meanwhile, their inherent drawbacks could be significantly reduced. Case studies are undertaken which verify the effectiveness and superiority of PER-SFC compared to that of other classical methods.     

永磁直驱风力发电机自抗扰技术及其无位置传感器控制策略

针对永磁直驱风力发电机传统矢量控制动态性能差,抗扰动能力弱的问题,提出一种双环线性自抗扰控制系统。在此基础上针对传统滑模观测器抖振等因素造成的速度和位置角观测误差较大的问题,提出改进型自适应滑模观测器。结果表明所设计的速度和电流双环线性自抗扰控制策略能有效提高转速跟踪性能和电流波形质量;在滑模观测器的基础上结合自适应算法精确观测反电动势,借鉴锁相环原理代替反正切函数估算出转子转速和位置角,相比传统滑模观测器具有更高的估算精度。     

Study on the control strategy for a boost converter used in hybrid energy storage system of electric vehicles

升压型直流变换器采用滑模变结构控制策略存在收敛速度较慢、抖振剧烈等导致的动态响应品质差问题。本文提出一种双幂次滑模趋近滞环控制策略,在电流跟踪误差估计值的基础上定义滑模面以实现电流跟踪控制,依据系统的未知扰动和负载变化建立自适应状态观测器,结合李雅普诺夫函数设计自适应律,并计算自适应占空比。提出一种双幂次趋近律,根据系统不同趋近过程的特点制定参数选择标准,对系统的动态响应品质进行目的性调节,并设计滑模滞环控制器以削弱由符号函数项所引起的抖振。对以上方法进行了仿真验证,结果显示可有效改善系统的动态特性和电流控制鲁棒性。     

Speed-sensorless torque control of induction machine based on carrier signal injection and smooth-air-gap induction machine model

A speed-estimation technique for induction machines, based on carrier signal injection and the standard two-axis smooth-air-gap induction machine model, is presented. The proposed speed-estimation technique can work over a wide range of operating points, including fundamental dc excitation. The stability of the algorithm is analyzed using a two-time-scale approach. Based on the estimated rotor speed, a torque controller is designed. Experimental results are presented confirming the validity of this approach. A method to reduce torque ripple generated by the injected carrier signals is also introduced.     

SSCI mitigation of grid‐connected DFIG wind turbines with fractional‐order sliding mode controller

To mitigate subsynchronous control interaction (SSCI) in doubly fed induction generator (DFIG)‐based wind farm, this paper proposes a robust controller for rotor‐side converter (RSC) using fractional‐order sliding mode controller (FOSMC). The proposed FOSMC can improve robustness and convergence properties of the controlled system, thus achieving SSCI damping under various operating conditions. Impedance‐based analysis and time‐domain simulation are performed to check the capability of the designed FOSMC as compared with conventional sliding mode control (SMC) and subsynchronous damping control (SSDC). Simulation results demonstrate that FOSMC can mitigate SSCI within shorter time and effectively reduce the fluctuation range of system transient responses under various operating conditions of wind speeds and compensation levels. Moreover, FOSMC also improves system robustness against parameter uncertainties and external disturbances, which is important for safe operation of realistic wind farms.     

A novel nonlinear observer‐based LQ control system design for wind energy conversion systems with single measurement

The issue of tracking the optimal power for wind energy conversion systems (WECSs) via regulating the rotor speed of the generator is taken into account in this study. Additionally, a novel polynomial observer is proposed for estimating not only aerodynamic torque in WECSs but also d‐axis and electromagnetic torque. Therefore, in this new approach, only the rotor speed of the generator is required to be measured instead of measuring all state variables. With the new observer form, the aerodynamic torque does not need to satisfy any constraints, which are mandatory in the previous methods. It should be noted that this methodology has not been investigated for the WECSs in any previous papers. To design a complete control system, a linear optimal control method cooperated with the polynomial observer is employed to track the optimal trajectory of a generator. Moreover, in this paper, the permanent magnet synchronous generator is used. In addition, on the basis of the Lyapunov theory and sum‐of‐square (SOS) technique, the conditions for observer synthesis are derived in the main theorems. Finally, the simulation results are provided to prove the effectiveness and merit of the proposed method.     

Passivity-based sliding mode position control for induction motor drives

In this paper, a passivity-based sliding-mode controller is proposed to control the motion of an induction motor. At first, the induction motor is proved to be a state strictly passive system. Then, a sliding-mode position controller with an adaptive load torque estimator is designed to control the position of the induction motor such that the chattering effects associated with a classical sliding-mode position controller can be eliminated. The stability analysis of the overall position control system is carried out by the passivity theory. The proposed approach is robust with regard to variations of motor mechanical parameters and load torque disturbances. Finally, experimental results are included to demonstrate that good position tracking can be obtained without the rotor flux observer.     

Augmented LQG controller for enhancement of online dynamic performance for WTG system

Operation of variable speed wind turbine generator (WTG) in the above-rated region characterized by high turbulence intensities demands a trade-off between two performance metrics: maximization of energy harvested from the wind and minimization of damage caused by mechanical fatigue. This paper presents a learning adaptive controller for output power leveling and decrementing cyclic loads on the drive train. The proposed controller incorporates a linear quadratic Gaussian (LQG) augmented by a neurocontroller (NC) and regulates rotational speed by specifying the demanded generator torque. Pitch control ensures rated power output. A second-order model and a stochastic wind field model are used in the analysis. The LQG is used as a basis upon which the performance of the proposed paradigm in the trade-off studies is assessed. Simulation results indicate the proposed control scheme effectively harmonizes the relation between rotor speed and the highly turbulent wind speed thereby regulating shaft moments and maintaining rated power.     

Analysis and synthesis of sliding mode control for large scale variable speed wind turbine for power optimization

The problem of designing a nonlinear feedback control scheme for variable speed wind turbines, without wind speed measurements, in below rated wind conditions was addressed. The objective is to operate the wind turbines in order to have maximum wind power extraction while also the mechanical loads are reduced. Two control strategies were proposed seeking a better performance. The first strategy uses a tracking controller that ensures the optimal angular velocity for the rotor. The second strategy uses a Maximum Power Point Tracking (MPPT) algorithm while a non-homogeneous quasi-continuous high-order sliding mode controller is applied to ensure the power tracking. Two algorithms were developed to solve the tracking control problem for the first strategy. The first one is a sliding mode output feedback torque controller combined with a wind speed estimator. The second algorithm is a quasi-continuous high-order sliding mode controller to ensure the speed tracking. The proposed controllers are compared with existing control strategies and their performance is validated using a FAST model based on the Controls Advanced Research Turbine (CART). The controllers show a good performance in terms of energy extraction and load reduction.     

CFD simulation of a floating offshore wind turbine system using a variable-speed generator-torque controller

Prediction and control of rotor rotational velocity is critical for accurate aerodynamic loading and generator power predictions. A variable-speed generator-torque controller is combined with the two-phase CFD solver CFDShip-Iowa V4.5. The developed code is utilized in simulations of the 5 MW floating offshore wind turbine (FOWT) conceptualized by the National Renewable Energy Laboratory (NREL) for the Offshore Code Comparison Collaboration (OC3). Fixed platform simulations are first performed to determine baseline rotor velocity and developed torque. A prescribed platform motion simulation is completed to identify effects of platform motion on rotor torque. The OC3’s load case 5.1, with regular wave and steady wind excitation, is performed and results are compared to NREL’s OC3 results. The developed code is shown to functionally control generator speed and torque but requires controller calibration for maximum power extraction. Generator speed variance is observed to be a function of unsteady stream-wise platform motions. The increased mooring forces of the present model are shown to keep the turbine in a more favorable variable-speed control region. Lower overall platform velocity magnitudes and less rotor torque are predicted corresponding to lower rotor rotational velocities and a reduction in generated power. Potential improvements and modifications to the present method are considered.